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dc.contributor.authorStewart, M.
dc.contributor.authorLiu, W.
dc.contributor.authorCardell-Oliver, R.
dc.contributor.authorGriffin, Mark
dc.date.accessioned2018-06-29T12:27:00Z
dc.date.available2018-06-29T12:27:00Z
dc.date.created2018-06-29T12:09:04Z
dc.date.issued2017
dc.identifier.citationStewart, M. and Liu, W. and Cardell-Oliver, R. and Griffin, M. 2017. An interactive web-based toolset for knowledge discovery from short text log data, International Conference on Advanced Data Mining and Applications, pp. 853-858: Springer.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/68738
dc.identifier.doi10.1007/978-3-319-69179-4_61
dc.description.abstract

© Springer International Publishing AG 2017. Many companies maintain human-written logs to capture data on events such as workplace incidents and equipment failures. However, the sheer volume and unstructured nature of this data prevent it from being utilised for knowledge acquisition. Our web-based prototype software system provides a cohesive computational methodology for analysing and visualising log data that requires minimal human involvement. It features an interface to support customisable, modularised log data processing and knowledge discovery. This enables owners of event-based datasets containing short textual descriptions, such as occupational health & safety officers and machine operators, to identify latent knowledge not previously acquirable without significant time and effort. The software system comprises five distinct stages, corresponding to standard data mining milestones: exploratory analysis, data warehousing, association rule mining, entity clustering, and predictive analysis. To the best of our knowledge, it is the first dedicated system to computationally analyse short text log data and provides a powerful interface that visualises the analytical results and supports human interaction.

dc.publisherSpringer
dc.titleAn interactive web-based toolset for knowledge discovery from short text log data
dc.typeConference Paper
dcterms.source.volume10604 LNAI
dcterms.source.startPage853
dcterms.source.endPage858
dcterms.source.titleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dcterms.source.seriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dcterms.source.isbn978-3-319-69178-7
dcterms.source.conferenceInternational Conference on Advanced Data Mining and Applications
dcterms.source.placeSingapore
curtin.departmentSchool of Management
curtin.accessStatusFulltext not available


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